What is meant by "ground truth" in the context AI?
In the context of ML, ground truth refers to information provided by direct observation (empirical evidence). If you're training an algorithm to classify your data, then the ground truth will be the actual, true labels which could for example be manually annotated by an domain expert. Please note that the models prediction or the inferred labels, are not considered ground truth.